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.