Triple
T29054603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marriage and Love |
E735352
|
entity |
| Predicate | positionOnLove |
P17839
|
FINISHED |
| Object | distinguishes love from marriage |
—
|
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: distinguishes love from marriage | Statement: [Marriage and Love, positionOnLove, distinguishes love from marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnLove Context triple: [Marriage and Love, positionOnLove, distinguishes love from marriage]
-
A.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
B.
positionOnReason
chosen
Indicates that one entity holds a particular stance, justification, or rationale concerning another entity or issue.
-
C.
positionOften
Indicates that one entity frequently holds, occupies, or is located at a particular position relative to another entity or context.
-
D.
positionOnGood
Indicates the stance or viewpoint an entity holds regarding a particular good, such as support, opposition, or neutrality.
-
E.
positionA
Indicates the spatial or ordered position of an entity A within a defined reference frame or sequence.
- 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 28, 2026, 10:10 a.m.