Triple
T22773304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madā’in |
E563615
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
al-Nūbār
al-Nūbār is a locality or quarter within the ancient city complex of Madā’in, historically associated with the broader urban and cultural landscape of the region.
|
E1552943
|
NE FINISHED |
How this triple was built (4 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-Nūbār | Statement: [Madā’in, hasPart, al-Nūbār]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: al-Nūbār Context triple: [Madā’in, hasPart, al-Nūbār]
-
A.
An-Naziat
An-Naziat is the 79th chapter of the Qur'an, known for its vivid depiction of the Day of Resurrection and the fate of past nations.
-
B.
An-Naba
An-Naba is the 78th chapter of the Qur’an, known for its vivid depiction of the Day of Resurrection and the consequences of belief and disbelief.
-
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 Qarara
Al Qarara is a Palestinian town located in the southern Gaza Strip, known for its agricultural lands and proximity to the city of Khan Yunis.
-
E.
Al-Aar
Al-Aar is a famous Egyptian film featuring Adel Emam in a dramatic role that explores social and moral issues.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: al-Nūbār Triple: [Madā’in, hasPart, al-Nūbār]
Generated description
al-Nūbār is a locality or quarter within the ancient city complex of Madā’in, historically associated with the broader urban and cultural landscape of the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: al-Nūbār Target entity description: al-Nūbār is a locality or quarter within the ancient city complex of Madā’in, historically associated with the broader urban and cultural landscape of the region.
-
A.
An-Naziat
An-Naziat is the 79th chapter of the Qur'an, known for its vivid depiction of the Day of Resurrection and the fate of past nations.
-
B.
An-Naba
An-Naba is the 78th chapter of the Qur’an, known for its vivid depiction of the Day of Resurrection and the consequences of belief and disbelief.
-
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 Qarara
Al Qarara is a Palestinian town located in the southern Gaza Strip, known for its agricultural lands and proximity to the city of Khan Yunis.
-
E.
Al-Aar
Al-Aar is a famous Egyptian film featuring Adel Emam in a dramatic role that explores social and moral issues.
- F. None of above. chosen
Provenance (5 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b6040048190a36fa759e06136ea |
completed | April 29, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9822db848190b8498f7bc47bf7e2 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b98e33b78819084ac449dd47cc778 |
completed | May 18, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9996e05c8190ad2cb5704bb4c245 |
completed | May 18, 2026, 10:58 p.m. |
Created at: April 17, 2026, 3:27 p.m.