Triple
T37581092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Roi se meurt (stage role) |
E934959
|
entity |
| Predicate | relatedPlay |
P202249
|
FINISHED |
| Object | En attendant Godot |
E117439
|
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: En attendant Godot | Statement: [Le Roi se meurt (stage role), relatedPlay, En attendant Godot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedPlay Context triple: [Le Roi se meurt (stage role), relatedPlay, En attendant Godot]
-
A.
associatedDiscovery
Indicates that one entity is linked to, or involved in, the finding or uncovering of another entity.
-
B.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
C.
associatedShow
Indicates a relationship where one entity is linked or connected to a particular show (e.g., as its subject, source, or related program).
-
D.
associatedWithPlay
chosen
Indicates a relationship in which an entity is connected or linked to a particular play (theatrical work or dramatic performance) in some relevant way.
-
E.
relatedMatchType
Indicates that two entities are connected through a specified type or category of relationship that defines how they are considered related or matched.
- F. None of above.
Provenance (4 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40a7f565b08190916d318c897c19a9 |
completed | June 28, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.