Triple
T19014356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lazarus’ Tomb |
E465306
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | al-Eizariya |
—
|
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: al-Eizariya | Statement: [Lazarus’ Tomb, nearbySettlement, al-Eizariya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: al-Eizariya Context triple: [Lazarus’ Tomb, nearbySettlement, al-Eizariya]
-
A.
al-Eizariya
chosen
al-Eizariya is a Palestinian town on the southeastern outskirts of Jerusalem, historically identified with the biblical village of Bethany.
-
B.
Al-Ajurrī
Al-Ajurrī was a prominent early Islamic scholar and hadith compiler known for his influential works on Sunni creed, ethics, and traditions.
-
C.
Al-Azza
Al-Azza is a Palestinian refugee camp located near Bethlehem in the West Bank, known for its dense population and longstanding refugee community.
-
D.
Al-Haffah
Al-Haffah is a town in northwestern Syria known as an administrative center in the hilly, forested interior of the Latakia region.
-
E.
El-Radisiyah
El-Radisiyah is a town located in Egypt’s southern Aswan Governorate along the Nile Valley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6aac4dc8190ac51f22c13f1b96c |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:02 p.m.