Triple
T18913491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thamien |
E462662
|
entity |
| Predicate | hasAlternateName |
P39
|
FINISHED |
| Object | Tamien |
—
|
NE NERFINISHED |
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: Tamien | Statement: [Thamien, hasAlternateName, Tamien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tamien Context triple: [Thamien, hasAlternateName, Tamien]
-
A.
Tamien
chosen
Tamien is a Native American Ohlone tribe and language historically associated with the Santa Clara Valley region of California.
-
B.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
C.
Takabisha
Takabisha is a record-breaking steel roller coaster in Japan renowned for its extremely steep drop and intense thrill elements.
-
D.
Taiyan
Taiyan was an era name used during the reign of Emperor Taiwu of the Northern Wei dynasty in early medieval China.
-
E.
Tamahine
Tamahine is a 1963 British comedy film in which Nancy Kwan stars as a free-spirited Polynesian girl who disrupts life at an English boys' boarding school.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c624516c81909e6bf04707d3c71c |
completed | April 20, 2026, 6:22 a.m. |
Created at: April 10, 2026, 11:58 a.m.