Triple
T9005601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rob Carpenter |
E215135
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Carpenter |
E275002
|
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: Carpenter | Statement: [Rob Carpenter, familyName, Carpenter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carpenter Context triple: [Rob Carpenter, familyName, Carpenter]
-
A.
Carpenter
chosen
Carpenter is an occupational surname originally referring to someone who works with wood, now borne by many people across English-speaking countries.
-
B.
The Carpenter
The Carpenter is a painting by Dutch Golden Age artist Abraham Bloemaert, exemplifying his detailed and dramatic religious and genre scenes.
-
C.
Schrinner
Schrinner is a German-language surname most notably associated with Australian politician Adrian Schrinner, the Lord Mayor of Brisbane.
-
D.
Craftsman
Craftsman is a well-known American brand of tools, lawn and garden equipment, and workwear recognized for its durability and long association with home improvement and DIY projects.
-
E.
Woodshop
"Woodshop" is a song by the indie rock supergroup Nice As Fuck, known for its minimalist style and politically tinged, lo-fi sound.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc695afa34819086cf6fcce2997b5f |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e3f0c88190ae688632be25e5c9 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.