Triple
T8268154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Wolowitz |
E193352
|
entity |
| Predicate | friend |
P8712
|
FINISHED |
| Object | Penny |
E193351
|
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: Penny | Statement: [Howard Wolowitz, friend, Penny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penny Context triple: [Howard Wolowitz, friend, Penny]
-
A.
Penny
chosen
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."
-
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 the brave young orphan girl who is rescued by mice in Disney's animated adventure film "The Rescuers."
-
D.
Penny
Penny Pritzker is an American billionaire businesswoman, civic leader, and former U.S. Secretary of Commerce in the Obama administration.
-
E.
Penny
Penny is a character in Jim Jarmusch’s film "Broken Flowers," one of the former lovers visited by the protagonist during his cross-country journey.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb794fc4208190b268bc69ff2b28a9 |
completed | March 31, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd9505ecb08190bfe4025c858d7ef9 |
completed | April 1, 2026, 9:58 p.m. |
Created at: March 30, 2026, 5:50 p.m.