Triple
T19823820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aculco |
E476265
|
entity |
| Predicate | servesLocalCommuters |
P60095
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Aculco, servesLocalCommuters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesLocalCommuters Context triple: [Aculco, servesLocalCommuters, true]
-
A.
servesLocalTrains
chosen
Indicates that a station or facility provides service or stops specifically for local (non-express) train routes.
-
B.
commuterHubFor
Indicates a location that serves as a primary transit or gathering point for commuters traveling to or from another place.
-
C.
usedByCommuters
Indicates that something is regularly utilized by people traveling between home and work or school.
-
D.
hasCommuterServices
Indicates that a location or facility provides transportation services specifically intended for regular commuters, such as daily or frequent travelers between home and work or school.
-
E.
commuterMarket
Indicates a market or customer segment composed primarily of people who regularly commute, typically targeted based on their commuting patterns and needs.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6550070c4819099e1f057b9a8849e |
completed | April 20, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.