Triple
T9122965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mini |
E218900
|
entity |
| Predicate | friendshipWith |
P8712
|
FINISHED |
| Object | Afghan fruit seller |
—
|
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: Afghan fruit seller | Statement: [Mini, friendshipWith, Afghan fruit seller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: friendshipWith Context triple: [Mini, friendshipWith, Afghan fruit seller]
-
A.
hasFriendship
Indicates a mutual, positive social relationship of friendship existing between two entities.
-
B.
friend
chosen
Indicates a mutual, typically positive social relationship of companionship, trust, or support between two entities.
-
C.
childhoodFriend
Indicates that two people were close friends during their childhood period.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
acquaintanceOf
Indicates that one entity knows another in a casual or non-intimate way, without implying close friendship or strong personal ties.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:17 p.m.