Triple
T33026131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banu Yam |
E845046
|
entity |
| Predicate | borderPresence |
P30106
|
FINISHED |
| Object | Saudi–Yemeni borderlands |
—
|
NE NERFINISHED |
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: Saudi–Yemeni borderlands | Statement: [Banu Yam, borderPresence, Saudi–Yemeni borderlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderPresence Context triple: [Banu Yam, borderPresence, Saudi–Yemeni borderlands]
-
A.
borderRegionPresence
chosen
Indicates the presence or occurrence of something within or along a border region between areas or territories.
-
B.
borderAgencyPresent
Indicates that a border control or customs agency operates or is present at a given location or crossing point.
-
C.
crossBorderPresence
Indicates that an entity maintains operations, activities, or influence that extend across national or jurisdictional borders.
-
D.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
E.
borderEstablished
Indicates that a formal boundary between two geographic or political entities has been officially defined and put into effect.
- 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
Created at: May 1, 2026, 1:23 a.m.