Triple
T955530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Jersey rail network |
E20616
|
entity |
| Predicate | primaryGauge |
P21807
|
FINISHED |
| Object | standard gauge |
—
|
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: standard gauge | Statement: [South Jersey rail network, primaryGauge, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGauge Context triple: [South Jersey rail network, primaryGauge, standard gauge]
-
A.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
B.
primaryCriterion
Indicates that one factor is designated as the main or most important basis for a decision, judgment, or selection among alternatives.
-
C.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
D.
primaryGuidanceSystem
Indicates that one entity functions as the main or principal guidance or navigation system for another entity.
-
E.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
- F. None of above. chosen
Provenance (4 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3f7a7608190b8a8dd2486654bec |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.