Triple
T10540290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Azerbaijan Province |
E248676
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Ahar
Ahar is a historic city in northwestern Iran known as a regional center of the Azerbaijani population and a gateway to the Arasbaran forests.
|
E870967
|
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: Ahar | Statement: [East Azerbaijan Province, containsCity, Ahar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahar Context triple: [East Azerbaijan Province, containsCity, Ahar]
-
A.
Puzrish-Dagan
Puzrish-Dagan was a major Ur III-period Mesopotamian administrative center known for its extensive archive of economic and bureaucratic cuneiform tablets.
-
B.
Daimabad
Daimabad is an archaeological site in Maharashtra, India, notable for its late Harappan (Indus Valley Civilization) remains and distinctive Bronze Age artifacts.
-
C.
Tahara
Tahara is a feminine given name, often considered a variant of Tara, used in various cultures.
-
D.
Tahara
Tahara is a coastal city in central Japan known for its automotive manufacturing industry and scenic Cape Irago on the Atsumi Peninsula.
-
E.
Hapur
Hapur is a city in the Indian state of Uttar Pradesh, known as an industrial and grain market hub within the Delhi metropolitan area.
- 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: Ahar Triple: [East Azerbaijan Province, containsCity, Ahar]
Generated description
Ahar is a historic city in northwestern Iran known as a regional center of the Azerbaijani population and a gateway to the Arasbaran forests.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ahar Target entity description: Ahar is a historic city in northwestern Iran known as a regional center of the Azerbaijani population and a gateway to the Arasbaran forests.
-
A.
Puzrish-Dagan
Puzrish-Dagan was a major Ur III-period Mesopotamian administrative center known for its extensive archive of economic and bureaucratic cuneiform tablets.
-
B.
Daimabad
Daimabad is an archaeological site in Maharashtra, India, notable for its late Harappan (Indus Valley Civilization) remains and distinctive Bronze Age artifacts.
-
C.
Tahara
Tahara is a feminine given name, often considered a variant of Tara, used in various cultures.
-
D.
Tahara
Tahara is a coastal city in central Japan known for its automotive manufacturing industry and scenic Cape Irago on the Atsumi Peninsula.
-
E.
Hapur
Hapur is a city in the Indian state of Uttar Pradesh, known as an industrial and grain market hub within the Delhi metropolitan area.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a582be48190856c6f272eea4dcf |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9341d96c08190a6ba644b9acfe2c8 |
completed | April 10, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69d93802a4488190aa86ae209650d4e7 |
completed | April 10, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d938fcc3c48190a4acaaf75c1aa304 |
completed | April 10, 2026, 5:53 p.m. |
Created at: April 6, 2026, 12:32 p.m.