Triple
T5098001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tübatulabal people |
E114913
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Tübatulaba |
E320997
|
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: Tübatulaba | Statement: [Tübatulabal people, alsoKnownAs, Tübatulaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tübatulaba Context triple: [Tübatulabal people, alsoKnownAs, Tübatulaba]
-
A.
Tübatulabal
chosen
Tübatulabal is a Native American people and their Uto-Aztecan language traditionally associated with the Kern River region of California.
-
B.
Tabasaran
Tabasaran is a Northeast Caucasian language spoken primarily by the Tabasaran people in southern Dagestan, Russia.
-
C.
El Tebbin
El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
-
D.
Tuktukan
Tuktukan is a barangay (village-level administrative division) in the city of Taguig in Metro Manila, Philippines.
-
E.
Tutunamayanlar
Tutunamayanlar is a landmark Turkish novel by Oğuz Atay, celebrated for its experimental style, postmodern narrative, and incisive critique of modern Turkish society.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7567d21081909227ed8f08b74c71 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec363bfb88190a290b92d052a46ef |
completed | March 21, 2026, 4:12 p.m. |
Created at: March 20, 2026, 1:40 p.m.