Triple
T2269716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hal Ashby |
E50627
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Shampoo |
E125977
|
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: Shampoo | Statement: [Hal Ashby, notableWork, Shampoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shampoo Context triple: [Hal Ashby, notableWork, Shampoo]
-
A.
Shampoo
chosen
"Shampoo" is a 1975 satirical romantic comedy film set on the eve of the 1968 U.S. presidential election, starring Warren Beatty as a Beverly Hills hairdresser entangled in complex romantic and social relationships.
-
B.
Soap
Soap is a satirical American television sitcom that parodied daytime soap operas and became a cult classic for its controversial, boundary-pushing humor.
-
C.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
D.
Schwarzkopf
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
-
E.
Crest
Crest is a historic town in southeastern France’s Drôme department, best known for its medieval tower, one of the tallest castle keeps in Europe.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1bd376c8190a43decde599f62e6 |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d97a108190a26ffd20fac91a7e |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.