Triple
T5019167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Hopper |
E112806
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jim |
E24180
|
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: Jim | Statement: [Jim Hopper, givenName, Jim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Context triple: [Jim Hopper, givenName, Jim]
-
A.
Jim
chosen
Jim is a common English given name, typically used as a diminutive or familiar form of James.
-
B.
Joe
Joe is the given name of Joe Rosenthal, the American photographer famous for his iconic World War II image of the flag raising on Iwo Jima.
-
C.
Joe
Joe is the given name of Joe Nickell, an American investigator and author known for his work examining alleged paranormal and mysterious phenomena.
-
D.
Joe
Joe is a common masculine given name, often a short form of Joseph, used widely in English-speaking countries.
-
E.
Joe
"Joe" is a 1970 American drama film, directed by John G. Avildsen, that explores class conflict and reactionary violence through the unlikely alliance between a wealthy executive and a bigoted factory worker.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7342c62881909acb35849da8761c |
completed | March 20, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0ecf0d88190b459d9c29bfc005d |
completed | March 21, 2026, 2:53 p.m. |
Created at: March 20, 2026, 1:35 p.m.