Triple
T584971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upstate New York (broad sense) |
E15138
|
entity |
| Predicate | directionFrom |
P1101
|
FINISHED |
| Object | north of New York City metropolitan area |
—
|
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: north of New York City metropolitan area | Statement: [Upstate New York (broad sense), directionFrom, north of New York City metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: directionFrom Context triple: [Upstate New York (broad sense), directionFrom, north of New York City metropolitan area]
-
A.
primaryDirection
Indicates the main or dominant directional orientation associated with an entity or relation.
-
B.
frontLineDirection
Indicates the primary orientation or bearing in which the front line of a conflict, formation, or boundary is facing or advancing.
-
C.
orientation
chosen
Indicates the relative directional alignment or facing of one entity with respect to another or to a reference frame.
-
D.
forceDirection
Indicates the direction in which a force is applied or exerted in the relationship between entities.
-
E.
servesDirection
Indicates that one entity provides service or functionality oriented toward, or in the direction of, another 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9874c88190bd1e08d4689ea124 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.