Triple
T25845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porter |
E516
|
entity |
| Predicate | commuterRailPropulsion |
P1305
|
FINISHED |
| Object | diesel locomotives (Fitchburg Line) |
—
|
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: diesel locomotives (Fitchburg Line) | Statement: [Porter, commuterRailPropulsion, diesel locomotives (Fitchburg Line)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commuterRailPropulsion Context triple: [Porter, commuterRailPropulsion, diesel locomotives (Fitchburg Line)]
-
A.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
B.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
C.
rollingStockType
chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
D.
servedByRailroad
Indicates that a location or facility is provided with transportation or service by a railroad line or company.
-
E.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.