Triple
T3898722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come and Get It |
E90433
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Frank Shields |
E398194
|
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: Frank Shields | Statement: [Come and Get It, hasCastMember, Frank Shields]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Shields Context triple: [Come and Get It, hasCastMember, Frank Shields]
-
A.
Frank Shields
chosen
Frank Shields was an American amateur tennis champion and occasional film actor active in the 1930s.
-
B.
John McShain
John McShain was an American building contractor known for constructing major U.S. landmarks, including the Pentagon and significant parts of Washington, D.C.'s federal architecture.
-
C.
Max Dennison
Max Dennison is the skeptical teenage protagonist of the Halloween-themed fantasy film "Hocus Pocus," whose actions accidentally resurrect three witches in Salem.
-
D.
Sidney Badgley
Sidney Badgley was a Canadian-born architect known for designing prominent churches and public buildings across North America in the late 19th and early 20th centuries.
-
E.
Leslie Sharp
Leslie Sharp is a British social anthropologist known for her influential work on medical anthropology, organ transplantation, and the cultural politics of the body.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5285093208190a2ba00afcbd8a261 |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:21 p.m.