Triple
T16301878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma’an Governorate |
E395809
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Ma’an |
E568542
|
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: Ma’an | Statement: [Ma’an Governorate, largestCity, Ma’an]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma’an Context triple: [Ma’an Governorate, largestCity, Ma’an]
-
A.
Ma’an
chosen
Ma’an is a major city in southern Jordan that serves as an important regional hub and gateway to nearby desert and archaeological sites.
-
B.
Ramla
Ramla is an Israeli city historically significant as a major religious and communal center for Karaite Jews.
-
C.
Qalqilya
Qalqilya is a Palestinian city in the northwestern West Bank, known for being almost completely encircled by the Israeli West Bank barrier.
-
D.
Haifa
Haifa is a major Israeli city on the Mediterranean coast, known for its significant port, mixed Jewish-Arab population, and the terraced Baháʼí Gardens on Mount Carmel.
-
E.
Beit Lahia
Beit Lahia is a town in the northern Gaza Strip known for its agricultural lands and proximity to several major refugee camps.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e32da7081908d8bd320374a5731 |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003550fc0c8190ba78666da8b3cd81 |
completed | May 10, 2026, 7:35 a.m. |
Created at: April 10, 2026, 5:06 a.m.