Triple
T15595027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dancin’ with Tears in My Eyes |
E374869
|
entity |
| Predicate | hasBeenRecordedBy |
P9348
|
FINISHED |
| Object | Martha Tilton |
E936778
|
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: Martha Tilton | Statement: [Dancin’ with Tears in My Eyes, hasBeenRecordedBy, Martha Tilton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha Tilton Context triple: [Dancin’ with Tears in My Eyes, hasBeenRecordedBy, Martha Tilton]
-
A.
Martha Tilton
chosen
Martha Tilton was an American popular singer best known as a featured vocalist with Benny Goodman's band during the swing era of the late 1930s and 1940s.
-
B.
Martha Tilson
Martha Tilson is a vocalist best known for her work with the influential English post-punk band A Certain Ratio.
-
C.
Martha Dix
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
D.
Martha Pattridge
Martha Pattridge is known as the wife of longtime Manhattan District Attorney Robert M. Morgenthau.
-
E.
Martha Hunt
Martha Hunt is an American fashion model best known for her work with Victoria’s Secret, including serving as a Victoria’s Secret Angel.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff678536d48190a0192c79f7c281e7 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:12 a.m.