Triple
T2210078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles de Gaulle |
E50893
|
entity |
| Predicate | beamWaterline |
P37489
|
FINISHED |
| Object | approximately 31.5 metres |
—
|
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: approximately 31.5 metres | Statement: [Charles de Gaulle, beamWaterline, approximately 31.5 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beamWaterline Context triple: [Charles de Gaulle, beamWaterline, approximately 31.5 metres]
-
A.
hasBottomWater
Indicates that an entity contains or is associated with water specifically located at its bottom or lowest part.
-
B.
waterVolume
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
C.
waterBoard
Indicates subjecting someone to a form of torture that simulates drowning by pouring water over a cloth covering their face.
-
D.
transportsWaterTo
Indicates that one entity carries or conveys water from its location or source to another entity or destination.
-
E.
hasWaterBalance
Indicates that an entity maintains or exhibits a particular state or condition of water balance, such as hydration level or equilibrium between water intake and loss.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc1b912c08190b9d7bc9230e49d1d |
completed | March 7, 2026, 6:12 a.m. |
Created at: March 4, 2026, 7:46 p.m.