Triple
T6564757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lo-Toga |
E153874
|
entity |
| Predicate | glottologName |
P6521
|
FINISHED |
| Object | Lo-Toga |
E153874
|
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: Lo-Toga | Statement: [Lo-Toga, glottologName, Lo-Toga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lo-Toga Context triple: [Lo-Toga, glottologName, Lo-Toga]
-
A.
Lo-Toga
chosen
Lo-Toga is an Oceanic language spoken on the Torres Islands in northern Vanuatu.
-
B.
Boorga
Boorga is a small rural locality within the Hay Shire local government area in New South Wales, Australia.
-
C.
Hamutal
Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
-
D.
Lotso
Lotso is the strawberry-scented teddy bear who serves as the main antagonist in Pixar's animated film Toy Story 3.
-
E.
Tepiman
Tepiman is a subgroup of Uto-Aztecan languages spoken primarily in the southwestern United States and northern Mexico, including languages such as O'odham and Tepehuán.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae3b9ec8819080f3052556d95810 |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d5622e0481909b0ac0f4e06d19bc |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:52 p.m.