Triple
T13753495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lycian League |
E330414
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Isinda
Isinda was an ancient city in the region of Lycia, in what is now southwestern Turkey, known for participating in the Lycian League of city-states.
|
E1059609
|
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: Isinda | Statement: [Lycian League, hasMember, Isinda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isinda Context triple: [Lycian League, hasMember, Isinda]
-
A.
Ngundu
Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
-
B.
Orungu
Orungu is a dialect of the Myene language spoken by the Orungu people of coastal Gabon.
-
C.
Njaba
Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
-
D.
Zinza
The Zinza are an ethnic group primarily inhabiting areas around Lake Victoria in northwestern Tanzania, known for their Bantu language and fishing and farming traditions.
-
E.
Nganzai
Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
- 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: Isinda Triple: [Lycian League, hasMember, Isinda]
Generated description
Isinda was an ancient city in the region of Lycia, in what is now southwestern Turkey, known for participating in the Lycian League of city-states.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Isinda Target entity description: Isinda was an ancient city in the region of Lycia, in what is now southwestern Turkey, known for participating in the Lycian League of city-states.
-
A.
Ngundu
Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
-
B.
Orungu
Orungu is a dialect of the Myene language spoken by the Orungu people of coastal Gabon.
-
C.
Njaba
Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
-
D.
Zinza
The Zinza are an ethnic group primarily inhabiting areas around Lake Victoria in northwestern Tanzania, known for their Bantu language and fishing and farming traditions.
-
E.
Nganzai
Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a85813e88190a63fecf8b0675df6 |
completed | May 3, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69f7a968c3508190b1a86accb71b34cf |
completed | May 3, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7aa2f696081908f48d44bf7271abc |
completed | May 3, 2026, 8:03 p.m. |
Created at: April 9, 2026, 10:09 p.m.