Triple
T15411728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marseilles Lock and Dam |
E368609
|
entity |
| Predicate | lockChamberWidth |
P51574
|
FINISHED |
| Object | 110 feet |
—
|
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: 110 feet | Statement: [Marseilles Lock and Dam, lockChamberWidth, 110 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lockChamberWidth Context triple: [Marseilles Lock and Dam, lockChamberWidth, 110 feet]
-
A.
chamberSize
Indicates the relative capacity or dimensions of a chamber in relation to a specified reference or standard.
-
B.
hasChamberWidth
chosen
Indicates that an entity possesses a chamber whose width has a specified value or range.
-
C.
typeOfChamber
Indicates the specific kind or category of chamber that an entity belongs to or is classified as.
-
D.
chamber1
Indicates that an entity is a chamber or room, typically serving as an enclosed space within a larger structure.
-
E.
chamberType
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
- 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.