Triple
T2479537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady in the Dark |
E55179
|
entity |
| Predicate | firstRunDescription |
P25104
|
FINISHED |
| Object | commercially successful Broadway run |
—
|
LITERAL 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: commercially successful Broadway run | Statement: [Lady in the Dark, firstRunDescription, commercially successful Broadway run]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstRunDescription Context triple: [Lady in the Dark, firstRunDescription, commercially successful Broadway run]
-
A.
initialOpening
chosen
Indicates the first or earliest instance in which something is opened, begun, or made accessible.
-
B.
firstSessionStart
Indicates the point in time when an entity’s very first session or interaction begins.
-
C.
firstBlockMessage
Indicates that this is the initial message sent in the context of a blocking action or block-related interaction between entities.
-
D.
firstModuleLaunch
Indicates the event or relationship where the initial module of a system, project, or mission is launched or activated for the first time.
-
E.
firstTimeParticipation
Indicates that an entity is taking part in a specified event, activity, or context for the very first time.
- F. None of above.
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_69ab49e279e88190ab10d7248aea9d11 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.