Triple
T19071541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masbuta |
E466801
|
entity |
| Predicate | requiresRole |
P6843
|
FINISHED |
| Object | tarmida |
—
|
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: tarmida | Statement: [Masbuta, requiresRole, tarmida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tarmida Context triple: [Masbuta, requiresRole, tarmida]
-
A.
tarmida
chosen
A tarmida is an ordained Mandaean priest who performs religious rituals and guides the spiritual life of the Mandaean community.
-
B.
tundama
Tundama was a prominent Muisca ruler (cacique) known for leading resistance against the Spanish conquest in what is now central Colombia.
-
C.
tara iti
Tara iti is the Māori name for the critically endangered New Zealand fairy tern, one of Aotearoa’s rarest native seabirds.
-
D.
Tarama
Tarama is a small island municipality in Okinawa Prefecture, Japan, known for its subtropical climate, traditional Ryukyuan culture, and surrounding coral reefs.
-
E.
TAM
TAM is a Georgian aerospace company based in Tbilisi that designs, manufactures, and services aircraft and related aviation components.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19fa6948190bdf8e8ec022e12f2 |
completed | April 20, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:04 p.m.