Triple
T11984179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Bloom |
E285234
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object | Jenny Hill |
E300273
|
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: Jenny Hill | Statement: [Edward Bloom, hasFriend, Jenny Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenny Hill Context triple: [Edward Bloom, hasFriend, Jenny Hill]
-
A.
Jenny Hill
chosen
Jenny Hill is a character in the fantasy drama film "Big Fish," appearing as one of the many figures woven into Edward Bloom’s larger-than-life storytelling.
-
B.
Jenny Robertson
Jenny Robertson is an American actress known for her work in film and television, including roles in comedies and dramas since the 1980s.
-
C.
Jenny Healey
Jenny Healey is a person notable enough to be recognized as a significant bearer of the surname Healey.
-
D.
Jenny Nichols
Jenny Nichols is the daughter of Irish writer and socialite Annabel Davis-Goff and is associated with a prominent literary and artistic family.
-
E.
Jenny Halsey
Jenny Halsey is a fictional archaeologist and adventurer who serves as the female lead in the 2017 film "The Mummy."
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903973c848190aac871d6dfecc74b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ac420788190b12167aef7436c64 |
completed | May 3, 2026, 5:49 p.m. |
Created at: April 8, 2026, 9:46 p.m.