Triple
T589781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Subway |
E17240
|
entity |
| Predicate | hasTunnelSection |
P15152
|
FINISHED |
| Object | beneath Stockton Street |
—
|
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: beneath Stockton Street | Statement: [Central Subway, hasTunnelSection, beneath Stockton Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTunnelSection Context triple: [Central Subway, hasTunnelSection, beneath Stockton Street]
-
A.
hasTunnelLengthApprox
Indicates that an entity has a tunnel whose length is approximately a specified value.
-
B.
hasTollSegment
Indicates that a route, road, or path includes a segment where a toll must be paid.
-
C.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
D.
hasUndergroundSection
chosen
Indicates that an entity includes a portion or segment that is located below ground level.
-
E.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bb775fc819085b968f8615dca59 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.