Triple
T16671184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Can’t Stand Still |
E405107
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Lilah |
E815015
|
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: Lilah | Statement: [I Can’t Stand Still, hasTrack, Lilah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilah Context triple: [I Can’t Stand Still, hasTrack, Lilah]
-
A.
Lilah
chosen
Lilah is a feminine given name, often considered a modern, melodic variant of names like Lila or Delilah.
-
B.
Lilah Morgan
Lilah Morgan is a recurring antagonist in the TV series "Angel," known as a ruthless lawyer working for the demonic law firm Wolfram & Hart.
-
C.
Lila
Lila is the daughter of French actress Virginie Ledoyen.
-
D.
Lila
Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
-
E.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca175088190a0435422e13278c2 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091927a408190a612a9ae2fd30d0a |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:18 a.m.