Triple
T164998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GG1 electric locomotive |
E2993
|
entity |
| Predicate | lengthOverCouplers |
P266
|
FINISHED |
| Object | about 79 ft |
—
|
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: about 79 ft | Statement: [GG1 electric locomotive, lengthOverCouplers, about 79 ft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthOverCouplers Context triple: [GG1 electric locomotive, lengthOverCouplers, about 79 ft]
-
A.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
numberOfRivets
Indicates the quantitative relationship specifying how many rivets are associated with a given object or structure.
-
C.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
D.
seriesLengthMaximum
Indicates the maximum allowable or observed length (e.g., number of items or installments) in a series.
-
E.
numberOfRings
Indicates the quantity of rings associated with an entity.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258827da481909b20ea5e9d21676f |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25664ba8081908ac298511a9fc5ba |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.