Triple
T18432055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zabeel 1 |
E450294
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Zabeel
Zabeel is a prominent district in Dubai, United Arab Emirates, known for its royal palaces, expansive parks, and major landmarks such as Zabeel Park and the Dubai Frame.
|
E1324482
|
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: Zabeel | Statement: [Zabeel 1, locatedIn, Zabeel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zabeel Context triple: [Zabeel 1, locatedIn, Zabeel]
-
A.
Zubein
Zubein is a variant form of the given name Zubin, which is used as a personal name in various cultures.
-
B.
Zababdeh
Zababdeh is a predominantly Christian Palestinian town in the northern West Bank known as a local religious and educational center.
-
C.
Mahboula
Mahboula is a coastal residential district in the Ahmadi Governorate of Kuwait, known for its high-rise apartments and proximity to Kuwait City.
-
D.
Baniyas
Baniyas is a coastal city in northwestern Syria on the Mediterranean Sea, known for its port, oil refinery, and proximity to other Latakia Governorate towns.
-
E.
Baniyas
Baniyas is a professional football club based in the Baniyas area of Abu Dhabi in the United Arab Emirates, known for competing in the UAE Pro League.
- 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: Zabeel Triple: [Zabeel 1, locatedIn, Zabeel]
Generated description
Zabeel is a prominent district in Dubai, United Arab Emirates, known for its royal palaces, expansive parks, and major landmarks such as Zabeel Park and the Dubai Frame.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zabeel Target entity description: Zabeel is a prominent district in Dubai, United Arab Emirates, known for its royal palaces, expansive parks, and major landmarks such as Zabeel Park and the Dubai Frame.
-
A.
Zubein
Zubein is a variant form of the given name Zubin, which is used as a personal name in various cultures.
-
B.
Zababdeh
Zababdeh is a predominantly Christian Palestinian town in the northern West Bank known as a local religious and educational center.
-
C.
Mahboula
Mahboula is a coastal residential district in the Ahmadi Governorate of Kuwait, known for its high-rise apartments and proximity to Kuwait City.
-
D.
Baniyas
Baniyas is a coastal city in northwestern Syria on the Mediterranean Sea, known for its port, oil refinery, and proximity to other Latakia Governorate towns.
-
E.
Baniyas
Baniyas is a professional football club based in the Baniyas area of Abu Dhabi in the United Arab Emirates, known for competing in the UAE Pro League.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51b1771788190b26afdf65e9de502 |
completed | April 19, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03f0af8d008190a32d98e48208df37 |
completed | May 13, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_6a03f2f8800c8190b88f1d1971c4cc4c |
completed | May 13, 2026, 3:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03f3f1d64c8190b18269128d7e1f68 |
completed | May 13, 2026, 3:45 a.m. |
Created at: April 10, 2026, 11:26 a.m.