Triple
T15624605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didyme |
E375647
|
entity |
| Predicate | relationshipImpact |
P119483
|
FINISHED |
| Object | her death caused Marcus’s emotional withdrawal |
—
|
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: her death caused Marcus’s emotional withdrawal | Statement: [Didyme, relationshipImpact, her death caused Marcus’s emotional withdrawal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipImpact Context triple: [Didyme, relationshipImpact, her death caused Marcus’s emotional withdrawal]
-
A.
relationshipDynamic
Indicates a changing or evolving pattern of interaction between entities, such as shifts in their roles, closeness, or influence over time.
-
B.
relationshipFocus
Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
-
C.
relationshipToFriends
Indicates the type or nature of the relationship an entity has with its friends.
-
D.
basisOfRelationship
Indicates that one entity serves as the foundational reason, cause, or justification for the relationship that exists between two or more entities.
-
E.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9cfd94819091459aa17a002eaf |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:14 a.m.