Triple
T16068849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houston Dash |
E389806
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object |
Ted Segal
Ted Segal is an American real estate investor and sports executive best known as the principal owner of Houston’s professional soccer clubs, including the NWSL’s Houston Dash.
|
E256519
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ted Segal | Statement: [Houston Dash, owner, Ted Segal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Segal Context triple: [Houston Dash, owner, Ted Segal]
-
A.
Alex Segal
Alex Segal was an American film, television, and theater director active in the mid-20th century.
-
B.
Ben Straub
Ben Straub is a software developer and technical author best known for co-authoring the widely used Git reference book "Pro Git."
-
C.
Lloyd Segan
Lloyd Segan is an American television and film producer known for his work on genre and suspense projects, including the 2001 horror film "Bones."
-
D.
Joe Shavelson
Joe Shavelson was the husband of prominent labor activist and suffragist Clara Lemlich, known primarily in historical records through this association.
-
E.
Ben Schnetzer
Ben Schnetzer is an American actor known for his roles in films such as "Pride," "The Book Thief," and the fantasy epic "Warcraft."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ted Segal Triple: [Houston Dash, owner, Ted Segal]
Generated description
Ted Segal is an American real estate investor and sports executive best known as the principal owner of Houston’s professional soccer clubs, including the NWSL’s Houston Dash.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ted Segal Target entity description: Ted Segal is an American real estate investor and sports executive best known as the principal owner of Houston’s professional soccer clubs, including the NWSL’s Houston Dash.
-
A.
Ted Segal
chosen
Ted Segal is an American real estate investor and businessman best known as the majority owner of Major League Soccer club Houston Dynamo FC and the NWSL’s Houston Dash.
-
B.
Alex Segal
Alex Segal was an American film, television, and theater director active in the mid-20th century.
-
C.
Ben Straub
Ben Straub is a software developer and technical author best known for co-authoring the widely used Git reference book "Pro Git."
-
D.
Lloyd Segan
Lloyd Segan is an American television and film producer known for his work on genre and suspense projects, including the 2001 horror film "Bones."
-
E.
Joe Shavelson
Joe Shavelson was the husband of prominent labor activist and suffragist Clara Lemlich, known primarily in historical records through this association.
- F. None of above.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183bb98c88190ae4b5773358078be |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe480d59c8190962ac596a872b5e0 |
completed | May 10, 2026, 1:50 a.m. |
| NEDg | Description generation | batch_69ffe6ee34788190942ef1d3bb805f78 |
completed | May 10, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffe7d127848190bbd79a8b94a49f93 |
completed | May 10, 2026, 2:05 a.m. |
Created at: April 10, 2026, 4:57 a.m.