Triple
T654384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted |
E11614
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Ted (teddy bear) |
E11614
|
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: Ted (teddy bear) | Statement: [Ted, character, Ted (teddy bear)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted (teddy bear) Context triple: [Ted, character, Ted (teddy bear)]
-
A.
Ted
Ted is a masculine given name, often a diminutive of Theodore or Edward, commonly used in English-speaking countries.
-
B.
Ted
chosen
Ted is a 2012 comedy film about a foul-mouthed living teddy bear, created by and starring Seth MacFarlane.
-
C.
Stanley
Stanley is the given first name of Ann Dunham, the American anthropologist and mother of former U.S. President Barack Obama.
-
D.
Stanley
Stanley is a British noble family name historically associated with influential aristocrats, including Lord Stanley of Preston, who served as Governor General of Canada.
-
E.
Stanley
Stanley is an autonomous robotic vehicle developed by Stanford University that gained fame for winning the 2005 DARPA Grand Challenge, a landmark event in self-driving car research.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4bb5b881908a18b5ec1c94e0cf |
completed | March 1, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a591486b708190b0191e958c6c8851 |
completed | March 2, 2026, 1:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.