Triple
T1502908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thierry Henry |
E33834
|
entity |
| Predicate | goalsForFrance |
P29424
|
FINISHED |
| Object | 51 |
—
|
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: 51 | Statement: [Thierry Henry, goalsForFrance, 51]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalsForFrance Context triple: [Thierry Henry, goalsForFrance, 51]
-
A.
strengthFrance
Indicates a relationship where a level, measure, or attribute of strength is associated specifically with France.
-
B.
objectiveOfFrance
Indicates that something is an objective, goal, or aim pursued by France.
-
C.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
D.
timeUnderControlOfFrance
Indicates the period during which an entity was governed, administered, or otherwise under the political control of France.
-
E.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a90582f2548190bc0a6bdcd6d9d015 |
completed | March 5, 2026, 4:24 a.m. |
Created at: March 4, 2026, 7:24 p.m.