Triple
T21134280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Moore |
E520772
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ted |
—
|
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: Ted | Statement: [Ted Moore, givenName, Ted]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Context triple: [Ted Moore, givenName, Ted]
-
A.
Ted
chosen
Ted is a masculine given name, often a diminutive of Theodore or Edward, commonly used in English-speaking countries.
-
B.
Ted
Ted is a 2012 comedy film about a foul-mouthed living teddy bear, created by and starring Seth MacFarlane.
-
C.
Ted
Ted is the drummer best known for playing in the influential American punk rock band Dead Kennedys.
-
D.
Tom
Tom is a common masculine given name, often used in English-speaking countries as a short form of Thomas.
-
E.
Tony
Tony is the humanoid robot protagonist of Isaac Asimov’s science fiction short story “Satisfaction Guaranteed,” designed to interact closely with humans and explore the emotional and ethical implications of human–robot relationships.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235847948190984c7009ca7f6189 |
completed | April 21, 2026, 7:12 a.m. |
Created at: April 16, 2026, 2:56 p.m.