Triple
T10987331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilad al-Sham |
E259663
|
entity |
| Predicate | containsRegion |
P285
|
FINISHED |
| Object | Hauran |
E571616
|
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: Hauran | Statement: [Bilad al-Sham, containsRegion, Hauran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hauran Context triple: [Bilad al-Sham, containsRegion, Hauran]
-
A.
Hauran
chosen
Hauran is a historical region in southwestern Syria and northwestern Jordan, known for its fertile volcanic plains and ancient settlements.
-
B.
Harauti
Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
-
C.
Horki
Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
-
D.
Harestua
Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
-
E.
Roura
Roura is a commune in French Guiana known for its rainforest landscapes and proximity to the Kaw-Roura Marshland Nature Reserve.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b3c8388190be77e95d56979a7f |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344e9c66c81909163cea6aa9276e0 |
completed | April 18, 2026, 8:46 a.m. |
Created at: April 8, 2026, 9:24 p.m.