Triple
T22958791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alyson Lefebvré |
E570834
|
entity |
| Predicate | originalNetworkOfWork |
P2594
|
FINISHED |
| Object | Fox |
—
|
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: Fox | Statement: [Alyson Lefebvré, originalNetworkOfWork, Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fox Context triple: [Alyson Lefebvré, originalNetworkOfWork, Fox]
-
A.
Fox
Fox is a mischievous, tongue-twisting fox from Dr. Seuss’s children’s book "Fox in Socks," known for engaging in playful rhyming word games.
-
B.
Fox
chosen
Fox is a major American broadcast television network known for airing NFL games, including extensive coverage of NFC East matchups.
-
C.
Fox
The Fox were a Native American tribe of the Great Lakes region, closely allied with the Sauk and known for their resistance to U.S. expansion during the 18th and 19th centuries.
-
D.
Fox
Fox is a highly skilled and enigmatic assassin portrayed by Angelina Jolie in the 2008 action film "Wanted."
-
E.
Fox
Fox was a 19th-century British exploration vessel notably used in Arctic expeditions, including searches for the lost Franklin expedition.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f2ce9c8190977f146771816341 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.