Triple
T5143022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McG |
E116003
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Charlie's Angels |
E312396
|
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: Charlie's Angels | Statement: [McG, directed, Charlie's Angels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie's Angels Context triple: [McG, directed, Charlie's Angels]
-
A.
Charlie’s Angels: Full Throttle
Charlie’s Angels: Full Throttle is a 2003 action-comedy film sequel featuring the crime-fighting trio of private investigators in a high-energy, stunt-filled adventure.
-
B.
Charlie’s Angels (2019 film)
chosen
Charlie’s Angels (2019 film) is a 2019 action-comedy reboot of the spy franchise that follows a new generation of female private investigators working for the mysterious Charles Townsend.
-
C.
Bel-Air
Bel-Air is a Paris Métro station located in the 12th arrondissement of Paris, France.
-
D.
Bel-Air
Bel-Air is an upscale residential and commercial barangay in Makati City, Metro Manila, known for its gated villages and proximity to the central business district.
-
E.
Bel-Air
Bel-Air is a central public transport interchange in Geneva, Switzerland, serving as a key node for tram and bus connections across the city.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7883004881909c763da818d9b6e2 |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee07016e4819094aacafec653e700 |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:43 p.m.