Triple
T94464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Rogers |
E1898
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Ted |
E7779
|
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 | Statement: [Ted Rogers, nickname, Ted]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Context triple: [Ted Rogers, nickname, 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.
Timothy
Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
-
D.
Carl
Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
-
E.
Dennis
Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24fd4777c81909ea9b9a6bd4f7ad5 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2981ed378819099ef3fbff2236a94 |
completed | Feb. 28, 2026, 7:24 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.