Triple
T645257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankara |
E11226
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object |
Angora
Angora is the former Western name for Ankara, the capital city of modern Turkey.
|
E80641
|
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: Angora | Statement: [Ankara, formerName, Angora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angora Context triple: [Ankara, formerName, Angora]
-
A.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
-
B.
Larkana
Larkana is a major city in Pakistan known for its historical significance, including proximity to the ancient Indus Valley site of Mohenjo-daro and its association with the Bhutto political family.
-
C.
Avusy
Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
-
D.
Ballana
Ballana is an important archaeological site in Lower Nubia known for its rich group of royal tumulus graves from the post-Meroitic period.
-
E.
Lazistan
Lazistan is a historical coastal region along the southeastern Black Sea, traditionally inhabited by the Laz people and now largely within northeastern Turkey and parts of Georgia.
- 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: Angora Triple: [Ankara, formerName, Angora]
Generated description
Angora is the former Western name for Ankara, the capital city of modern Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Angora Target entity description: Angora is the former Western name for Ankara, the capital city of modern Turkey.
-
A.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
-
B.
Larkana
Larkana is a major city in Pakistan known for its historical significance, including proximity to the ancient Indus Valley site of Mohenjo-daro and its association with the Bhutto political family.
-
C.
Avusy
Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
-
D.
Ballana
Ballana is an important archaeological site in Lower Nubia known for its rich group of royal tumulus graves from the post-Meroitic period.
-
E.
Lazistan
Lazistan is a historical coastal region along the southeastern Black Sea, traditionally inhabited by the Laz people and now largely within northeastern Turkey and parts of Georgia.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f19f9a08190b0bf6e19b32427ff |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a57b5a0c0c81909aa3339d7ba62a0d |
completed | March 2, 2026, 11:58 a.m. |
| NEDg | Description generation | batch_69a57dbf6b1c8190981f9d85f721a7db |
completed | March 2, 2026, 12:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a57e2762908190957f71686d107483 |
completed | March 2, 2026, 12:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.