Triple
T38290056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margot |
E1022331
|
entity |
| Predicate | weaponizes |
P820
|
FINISHED |
| Object | customer service expectations |
—
|
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: customer service expectations | Statement: [Margot, weaponizes, customer service expectations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weaponizes Context triple: [Margot, weaponizes, customer service expectations]
-
A.
weaponizedAs
Indicates that something has been adapted, modified, or used for the purpose of causing harm, damage, or coercion, effectively turning it into a weapon.
-
B.
weaponsUsed
chosen
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
C.
laterWeaponizedBy
Indicates that something was subsequently developed, adapted, or used as a weapon by a specified agent or group.
-
D.
weaponizationStage
Indicates the phase or level of progress an entity or agent has reached in developing, adapting, or deploying something for use as a weapon.
-
E.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
- 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_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:30 p.m.