Triple
T3406706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spencer |
E71790
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Spenser |
E98292
|
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: Spenser | Statement: [Spencer, hasVariant, Spenser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spenser Context triple: [Spencer, hasVariant, Spenser]
-
A.
Campion
Campion is a surname most notably associated with New Zealand film director and screenwriter Jane Campion, acclaimed for works such as "The Piano."
-
B.
Edmund Spenser
chosen
Edmund Spenser was a major English Renaissance poet best known for his epic allegorical poem "The Faerie Queene."
-
C.
Arthur Brooke
Arthur Brooke was a 16th-century English poet best known for writing the narrative poem that served as the primary source for Shakespeare’s "Romeo and Juliet."
-
D.
Sir Philip Sidney
Sir Philip Sidney was a 16th-century English poet, courtier, and soldier renowned for works like "Astrophel and Stella" and "The Defence of Poesy."
-
E.
Mr. Dryden
Mr. Dryden is a British government official in the film "Lawrence of Arabia" who helps orchestrate T.E. Lawrence’s assignment in the Arab Revolt.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8ec68c88190913df5f6cafad9e9 |
completed | March 8, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bd8c0ec8190bd44d33fc031c845 |
completed | March 12, 2026, 11:27 p.m. |
Created at: March 8, 2026, 3:15 p.m.