Triple
T9923554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Cash Penney |
E187861
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Penney |
E187861
|
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: Penney | Statement: [James Cash Penney, familyName, Penney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penney Context triple: [James Cash Penney, familyName, Penney]
-
A.
Penney
chosen
Penney is the surname of James Cash Penney, the American businessman who founded the J. C. Penney department store chain.
-
B.
Penny
Penny is the given name of American actress Penny Johnson Jerald, known for her roles in series such as "24" and "Star Trek: Deep Space Nine."
-
C.
Penny
Penny is a fictional character appearing in the science fiction novel "Timescape" by Gregory Benford.
-
D.
Penny
Penny is a friendly, aspiring actress and waitress who becomes the sociable, down-to-earth neighbor and later close friend and love interest of the main nerdy characters in the sitcom "The Big Bang Theory."
-
E.
Penny
Penny Pritzker is an American billionaire businesswoman, civic leader, and former U.S. Secretary of Commerce in the Obama administration.
- 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_69ca82b22a688190b52c75bd48429c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb59733188190900426e4e29ae5e3 |
completed | April 2, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d2e676c81909e4eed258ecdf053 |
completed | April 5, 2026, 10:45 a.m. |
Created at: March 30, 2026, 8:43 p.m.