Triple
T18330301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarana Burke |
E439119
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tarana |
—
|
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: Tarana | Statement: [Tarana Burke, givenName, Tarana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarana Context triple: [Tarana Burke, givenName, Tarana]
-
A.
Tarana
chosen
Tarana is the first name of Tarana Burke, the American civil rights activist who founded the Me Too movement.
-
B.
Tamaran
Tamaran is a fictional alien planet in the DC Comics universe, best known as the war-torn, sun-powered home of the superheroine Starfire and her people, the Tamaraneans.
-
C.
Arnara
Arnara is a small municipality in the Lazio region of central Italy, located in the province of Frosinone.
-
D.
Tenea
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
-
E.
Derisha
Derisha is a lexical form or word used in a linguistic context, likely representing one member of a pair of related terms alongside Perisha.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ec900808190bc4468270e0957c1 |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.