Triple
T122000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAX Red Line |
E2466
|
entity |
| Predicate | trackConfiguration |
P3832
|
FINISHED |
| Object | mostly double track |
—
|
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: mostly double track | Statement: [MAX Red Line, trackConfiguration, mostly double track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackConfiguration Context triple: [MAX Red Line, trackConfiguration, mostly double track]
-
A.
trackType
chosen
Indicates the specific kind or category of track associated with an entity, such as its functional or physical classification.
-
B.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
C.
tracks
Indicates that one entity monitors, follows, or keeps a record of another entity’s state, behavior, or progress over time.
-
D.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
E.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a25739ef28819093f3f0e6bb670201 |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564928208190966a619680a0d6e2 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.