Triple
T24006849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Year of the Snake |
E594411
|
entity |
| Predicate | associatedLuckyNumber |
P154834
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Year of the Snake, associatedLuckyNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLuckyNumber Context triple: [Year of the Snake, associatedLuckyNumber, 2]
-
A.
numbersDrawnLuckyStars
Indicates that the specified numbers are the ones selected as the "lucky stars" in a draw or lottery-style event.
-
B.
GoldenBallWinner
Indicates that the subject has been awarded the Golden Ball, recognizing them as the best-performing player in a particular football (soccer) tournament or competition.
-
C.
LuckySevenPredecessorGame
Indicates a game-related relationship where one entity is the immediate predecessor of another in a sequence or state transition specifically associated with a "lucky seven" condition or rule.
-
D.
associatedSingle
Indicates a one-to-one association where an entity is linked to exactly one corresponding related entity.
-
E.
imoNumber
Indicates that an entity is associated with a specific International Maritime Organization (IMO) identification number used to uniquely identify ships and certain maritime structures.
- 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_69e288b9ecf08190b8c94a278f5674fe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d46a6ba48190b0cce0b134dfb35f |
completed | April 29, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:40 p.m.