Triple
T5593242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheke Holo |
E146931
|
entity |
| Predicate | glottologName |
P6521
|
FINISHED |
| Object | Cheke Holo |
E146931
|
NE FINISHED |
How this triple was built (2 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: Cheke Holo | Statement: [Cheke Holo, glottologName, Cheke Holo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheke Holo Context triple: [Cheke Holo, glottologName, Cheke Holo]
-
A.
Cheke Holo
chosen
Cheke Holo is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
-
B.
Checca
Checca is an Italian diminutive form of the female given name Francesca, commonly used as an affectionate nickname.
-
C.
Joyo
Joyo is a small city in Japan known for its location in Kyoto Prefecture and its blend of residential areas, light industry, and historical sites.
-
D.
Honancho
Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
-
E.
Chenek
Chenek is a small highland settlement in Ethiopia’s Simien Mountains, commonly used as a base for trekking and accessing the nearby peak of Ras Dashen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020bb08648190ab1f66cc3e897e6d |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0286b4d2c8190a3224f3082316dc8 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:38 p.m.