Triple
T15942867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hala Haveli |
E386608
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Hala |
E303394
|
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: Hala | Statement: [Hala Haveli, locatedNear, Hala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hala Context triple: [Hala Haveli, locatedNear, Hala]
-
A.
Hala
chosen
Hala is a feminine given name of Arabic origin commonly used across the Middle East and among Arabic-speaking communities worldwide.
-
B.
Nahila
Nahila is a character from the novel "Gate of the Sun," which portrays the Palestinian experience through interwoven personal and historical narratives.
-
C.
Hanan
Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
-
D.
Halafta
Halafta was a tannaic sage of the early rabbinic period, best known as the father of Rabbi Yose ben Halafta.
-
E.
Hala Pisana
Hala Pisana is a scenic mountain meadow in Poland’s Tatra Mountains, known for its picturesque alpine landscapes and traditional pastoral character.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156cefe948190af40eac92983edbc |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5bbc07c819098fd768e2e6b5b3e |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.