Triple
T3379346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Fontana |
E71142
|
entity |
| Predicate | wroteFor |
P1996
|
FINISHED |
| Object | Copper |
E352422
|
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: Copper | Statement: [Tom Fontana, wroteFor, Copper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Copper Context triple: [Tom Fontana, wroteFor, Copper]
-
A.
Copper
Copper is one of the animal mascots created to represent and promote the 2002 Winter Olympics in Salt Lake City.
-
B.
Copper
chosen
Copper is a period crime drama television series set in 19th-century New York City, created by Tom Fontana and others.
-
C.
copper (chemical element)
Copper is a reddish-brown, highly conductive metallic element widely used in electrical wiring, electronics, and alloys such as bronze and brass.
-
D.
Nickel
Nickel is a chemical element and transition metal known for its hardness, corrosion resistance, and widespread use in alloys and batteries.
-
E.
Brass
Brass is a coastal local government area and historic town in Bayelsa State, Nigeria, known for its role in the Niger Delta’s oil and gas activities and its traditional trading heritage.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2ec38d88190be8c824daeca5ab6 |
completed | March 8, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b35460b4a081908f05bf786cc9bcd3 |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 8, 2026, 3:14 p.m.