Triple
T3433274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renny Harlin |
E72388
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Renny |
E159496
|
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: Renny | Statement: [Renny Harlin, givenName, Renny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renny Context triple: [Renny Harlin, givenName, Renny]
-
A.
Renny
chosen
Renny is a diminutive or short form of the given name René, often used as a familiar or affectionate variant.
-
B.
Retta
Retta is an American actress and comedian best known for her roles on the television series "Parks and Recreation" and "Good Girls."
-
C.
Maxene Reynolds
Maxene Reynolds is the daughter of legendary American actress and singer Debbie Reynolds.
-
D.
Kay Nelson
Kay Nelson was a Hollywood costume designer known for her work on classic films of the 1940s.
-
E.
Marilu Henner
Marilu Henner is an American actress and author best known for her role as Elaine Nardo on the TV sitcom "Taxi" and for her appearances in numerous film and television projects.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9c1d9148190b873ba66d34d4f01 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360cbcb60819095a28e50cac5a4ca |
completed | March 13, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:15 p.m.