Triple
T1988507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemeni corner |
E43195
|
entity |
| Predicate | oppositeCorner |
P3232
|
FINISHED |
| Object | Iraqi corner |
—
|
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: Iraqi corner | Statement: [Yemeni corner, oppositeCorner, Iraqi corner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oppositeCorner Context triple: [Yemeni corner, oppositeCorner, Iraqi corner]
-
A.
locatedAtCornerOf
Indicates that one entity is positioned at or forms the corner where two or more boundaries, edges, or intersecting paths meet.
-
B.
opposingLocation
chosen
Indicates that two entities are located directly opposite each other, typically across a defined reference such as a street, corridor, or boundary.
-
C.
oppositeLatitude
Indicates that one entity is located at the same longitude as another but at the latitude that is equal in magnitude and opposite in sign (i.e., mirrored across the equator).
-
D.
cornerOfTriangle
Indicates that the subject is a vertex (corner point) belonging to a specific triangle.
-
E.
oppositeNumber
Indicates that one number is the additive inverse of the other, such that their sum equals zero.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.