Triple
T15411730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marseilles Lock and Dam |
E368609
|
entity |
| Predicate | numberOfDamGates |
P21387
|
FINISHED |
| Object | multiple tainter gates |
—
|
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: multiple tainter gates | Statement: [Marseilles Lock and Dam, numberOfDamGates, multiple tainter gates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDamGates Context triple: [Marseilles Lock and Dam, numberOfDamGates, multiple tainter gates]
-
A.
numberOfDams
Indicates the quantity of dams associated with or present in a given entity or context.
-
B.
hasSpillwayGates
Indicates that a structure, typically a dam or spillway, is equipped with one or more controllable gates for regulating water flow.
-
C.
numberOfGates
chosen
Indicates the quantity of gates associated with or belonging to an entity.
-
D.
hasLockAndDamSystem
Indicates that one entity possesses or is equipped with a system of locks and dams used to control water levels and facilitate navigation.
-
E.
lengthOfEachGate
Indicates the measurement of the individual length associated with each gate in a set or system.
- F. None of above.
Provenance (3 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea600b48190a3dbca1a68a2a1cd |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.