Triple
T17990754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Child 44 |
E430362
|
entity |
| Predicate | literaryAwardShortlist |
P130039
|
FINISHED |
| Object | Man Booker Prize longlist |
—
|
LITERAL FINISHED |
How this triple was built (2 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: Man Booker Prize longlist | Statement: [Child 44, literaryAwardShortlist, Man Booker Prize longlist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryAwardShortlist Context triple: [Child 44, literaryAwardShortlist, Man Booker Prize longlist]
-
A.
sharesBookerPrizeWith
Indicates that two entities have both received the Booker Prize, sharing this literary award in common.
-
B.
awardWithinFiction
Indicates that an award is given or exists within a fictional context or narrative world, rather than in real life.
-
C.
notableCoWinnersExample
Indicates that the related entities are notable examples of co-winners who shared the same award or recognition.
-
D.
awardNameIncludes
Indicates that the name of an award contains the specified text or substring.
-
E.
alsoAwardedIn
Indicates that the same award or recognition was given in an additional time, place, or context beyond the primary one.
- F. None of above. chosen
Provenance (4 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29f127c81908b0c4cb3787e002c |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:23 a.m.