Triple
T14358538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Perfect Guy |
E356035
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Tyger Williams
Tyger Williams is an American screenwriter best known for writing the acclaimed 1993 crime drama film "Menace II Society."
|
E1094752
|
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: Tyger Williams | Statement: [The Perfect Guy, screenwriter, Tyger Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyger Williams Context triple: [The Perfect Guy, screenwriter, Tyger Williams]
-
A.
Tyger Drew-Honey
Tyger Drew-Honey is a British actor and television presenter best known for his roles in the sitcoms "Outnumbered" and "Cuckoo."
-
B.
Wilder Williams
Wilder Williams is an individual notable enough to be recognized as a prominent bearer of the given name Wilder.
-
C.
Milan Williams
Milan Williams was an American keyboardist, songwriter, and founding member of the funk and soul band the Commodores.
-
D.
Teddy Walker
Teddy Walker is the charismatic, fast-talking protagonist of the comedy film "Night School," whose return to earn his GED drives the movie’s central story.
-
E.
Wyking Jones
Wyking Jones is an American basketball coach and former player best known for serving as the head coach of the University of California, Berkeley men's basketball program.
- 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: Tyger Williams Triple: [The Perfect Guy, screenwriter, Tyger Williams]
Generated description
Tyger Williams is an American screenwriter best known for writing the acclaimed 1993 crime drama film "Menace II Society."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tyger Williams Target entity description: Tyger Williams is an American screenwriter best known for writing the acclaimed 1993 crime drama film "Menace II Society."
-
A.
Tyger Drew-Honey
Tyger Drew-Honey is a British actor and television presenter best known for his roles in the sitcoms "Outnumbered" and "Cuckoo."
-
B.
Wilder Williams
Wilder Williams is an individual notable enough to be recognized as a prominent bearer of the given name Wilder.
-
C.
Milan Williams
Milan Williams was an American keyboardist, songwriter, and founding member of the funk and soul band the Commodores.
-
D.
Teddy Walker
Teddy Walker is the charismatic, fast-talking protagonist of the comedy film "Night School," whose return to earn his GED drives the movie’s central story.
-
E.
Wyking Jones
Wyking Jones is an American basketball coach and former player best known for serving as the head coach of the University of California, Berkeley men's basketball program.
- F. None of above. chosen
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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c48dd408190ac45ad4ca6f610c3 |
completed | May 8, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69fd4cf6e6788190a98479ed3b615a4e |
completed | May 8, 2026, 2:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4d6dd7c481908f53f8902ee714dd |
completed | May 8, 2026, 2:41 a.m. |
Created at: April 10, 2026, 1:15 a.m.