Triple
T3287952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xenophon’s Symposium |
E69030
|
entity |
| Predicate | containsScene |
P47737
|
FINISHED |
| Object | conversation about eros (love) |
—
|
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: conversation about eros (love) | Statement: [Xenophon’s Symposium, containsScene, conversation about eros (love)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsScene Context triple: [Xenophon’s Symposium, containsScene, conversation about eros (love)]
-
A.
hasInfluenceFromScene
Indicates that something is affected, shaped, or guided by the characteristics or context of a particular scene.
-
B.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
-
C.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
D.
associatedWithGenreScene
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader genre.
-
E.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
- F. None of above. chosen
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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb058e00881908fdf0a23208860d4 |
completed | March 8, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69ada421fadc8190b7c7d3c8afd20061 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada526764881908e4bd52938d5374d |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:10 p.m.