Triple
T4000666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilead |
E89405
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Bashan |
E383136
|
NE 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: Bashan | Statement: [Gilead, borderedBy, Bashan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bashan Context triple: [Gilead, borderedBy, Bashan]
-
A.
Bashan
chosen
Bashan is a historically significant region east of the Jordan River, renowned in biblical texts for its fertile lands, strong cities, and mighty cattle.
-
B.
Shushan
Shushan is the ancient Persian royal city traditionally identified as the capital where the events of the biblical Book of Esther take place.
-
C.
Haran
Haran is an ancient city in northern Mesopotamia known from the Hebrew Bible as a key dwelling place of the patriarch Abraham before his journey to Canaan.
-
D.
Shabara
Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
-
E.
Khar
Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa417c408190a9aa4875e417011d |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c5b17c48190b8fd2a6728a65b10 |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:34 p.m.