Triple
T14195885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talia Shire |
E351833
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Rocky |
E10224
|
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: Rocky | Statement: [Talia Shire, notableWork, Rocky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rocky Context triple: [Talia Shire, notableWork, Rocky]
-
A.
Rocky
chosen
Rocky is a classic 1976 American sports drama film starring Sylvester Stallone as an underdog boxer who gets an unlikely shot at the world heavyweight title.
-
B.
Rocky
Rocky is the nickname of Rocky Wirtz, the late principal owner and chairman of the NHL’s Chicago Blackhawks.
-
C.
Rocky
Rocky is a Hindi-language Bollywood film featuring Indian cinema icon Shammi Kapoor in a prominent role.
-
D.
Rocky
Rocky is the given name of American football coach Rocky Long, known for his long career leading various college teams.
-
E.
Rocky
Rocky is a fictional character named Rocky Thirteen Barker, commonly referred to by the given name Rocky.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e1fbd48190a4864fa4443f8f29 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd194b32d88190aa74eef576152db3 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:04 a.m.