Triple
T3433388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristen Stewart |
E72389
|
entity |
| Predicate | starredIn |
P1668
|
FINISHED |
| Object | Spencer |
E360742
|
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: Spencer | Statement: [Kristen Stewart, starredIn, Spencer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spencer Context triple: [Kristen Stewart, starredIn, Spencer]
-
A.
Spencer
Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
-
B.
Spencer
Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
-
C.
Spencer
chosen
Spencer is a 2021 biographical psychological drama film depicting Princess Diana during a tense Christmas holiday with the British royal family, starring Kristen Stewart in the lead role.
-
D.
Spencer
Spencer is the middle name of American author and aviator Anne Spencer Lindbergh, reflecting her family’s naming tradition.
-
E.
Jeremy Spenser
Jeremy Spenser is a British actor best known for his film and stage work in the 1950s and 1960s, including notable roles in classic British cinema.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9c1d9148190b873ba66d34d4f01 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373a2271081908816fbf6cac06975 |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:15 p.m.