Triple
T11465003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wedding Night |
E271756
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Esther Dale |
E683189
|
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: Esther Dale | Statement: [The Wedding Night, hasCastMember, Esther Dale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esther Dale Context triple: [The Wedding Night, hasCastMember, Esther Dale]
-
A.
Esther Dale
chosen
Esther Dale was an American character actress known for her numerous supporting roles in Hollywood films and early television from the 1930s through the 1950s.
-
B.
Esther Smith
Esther Smith is the central teenage daughter in the classic 1944 MGM musical film "Meet Me in St. Louis," famously portrayed by Judy Garland.
-
C.
Esther Harvey
Esther Harvey was the wife of renowned American Broadway baritone and actor Alfred Drake.
-
D.
Esther Ross
Esther Ross was the woman who served as the sponsor and ceremonial namesake figure for the U.S. Navy battleship USS Arizona (BB-39) at its christening.
-
E.
Esther Harper
Esther Harper is a character in the animated adventure film "The Sea Beast," depicted as a determined and courageous figure involved in the story’s high-seas monster-hunting exploits.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f5eb988190b309b8e309f6d1a5 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f165f5b3d081909c00144eb9291ff5 |
completed | April 29, 2026, 1:59 a.m. |
Created at: April 8, 2026, 9:35 p.m.