Triple
T15262533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Field |
E364817
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Hap-Hazard
Hap-Hazard is a notable work by American journalist and lecturer Kate Field, reflecting her wit and social commentary.
|
E1146678
|
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: Hap-Hazard | Statement: [Kate Field, notableWork, Hap-Hazard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hap-Hazard Context triple: [Kate Field, notableWork, Hap-Hazard]
-
A.
The Hazards
The Hazards are a striking line of pink granite mountains on Tasmania’s Freycinet Peninsula, known for their scenic coastal views and popular hiking trails.
-
B.
Lojinx
Lojinx is an independent British record label known for releasing power pop, indie, and alternative rock music.
-
C.
Happy Haines
Happy Haines is a fictional character portrayed by actor Allan "Ladd" See, best known from his work in mid-20th-century American film and television.
-
D.
Haps
Haps is a village in the Dutch province of North Brabant, now part of the municipality of Land van Cuijk.
-
E.
Hullabaloo
Hullabaloo was a 1960s American musical variety television show that featured popular rock and pop performers of the era.
- 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: Hap-Hazard Triple: [Kate Field, notableWork, Hap-Hazard]
Generated description
Hap-Hazard is a notable work by American journalist and lecturer Kate Field, reflecting her wit and social commentary.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hap-Hazard Target entity description: Hap-Hazard is a notable work by American journalist and lecturer Kate Field, reflecting her wit and social commentary.
-
A.
The Hazards
The Hazards are a striking line of pink granite mountains on Tasmania’s Freycinet Peninsula, known for their scenic coastal views and popular hiking trails.
-
B.
Lojinx
Lojinx is an independent British record label known for releasing power pop, indie, and alternative rock music.
-
C.
Happy Haines
Happy Haines is a fictional character portrayed by actor Allan "Ladd" See, best known from his work in mid-20th-century American film and television.
-
D.
Haps
Haps is a village in the Dutch province of North Brabant, now part of the municipality of Land van Cuijk.
-
E.
Hullabaloo
Hullabaloo was a 1960s American musical variety television show that featured popular rock and pop performers of the era.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084fed0481908e452c89cba2be82 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5fb8b30819096d31ba5884715c9 |
completed | May 9, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69fee805f5bc8190a6095e3c374f3441 |
completed | May 9, 2026, 7:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fee8e4dc688190bd597f8d710c8afc |
completed | May 9, 2026, 7:57 a.m. |
Created at: April 10, 2026, 3:14 a.m.