Triple
T4773343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duquesne Incline |
E105983
|
entity |
| Predicate | hasEngineRoom |
P6655
|
FINISHED |
| Object | upper station |
—
|
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: upper station | Statement: [Duquesne Incline, hasEngineRoom, upper station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEngineRoom Context triple: [Duquesne Incline, hasEngineRoom, upper station]
-
A.
hasCrewCompartmentMaterial
Indicates that an entity’s crew compartment is made of, or incorporates, a specified material.
-
B.
hasCentralTank
Indicates that an entity possesses or is equipped with a primary central tank as a key component or feature.
-
C.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
D.
hasFuelStorage
Indicates that one entity possesses or is equipped with a facility, container, or system used to store fuel for later use.
-
E.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6560b3448190a0debbd8da29d986 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.