Triple
T28156367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leah Burke |
E714758
|
entity |
| Predicate | hasInsecurity |
P194349
|
FINISHED |
| Object | body image |
—
|
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: body image | Statement: [Leah Burke, hasInsecurity, body image]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInsecurity Context triple: [Leah Burke, hasInsecurity, body image]
-
A.
hasSecurityConsideration
Indicates that there is a relevant security-related issue, risk, or precaution associated with the referenced entity.
-
B.
hasSecuritySignificance
Indicates that something possesses importance or impact in the context of security, such as affecting safety, protection, or risk levels.
-
C.
insecurityLinkedTo
Indicates a relationship where one entity’s insecurity is connected or attributed to another entity as a contributing factor or source.
-
D.
hasSecurityPresence
Indicates that some form of security personnel, system, or measures are present at or associated with an entity or location.
-
E.
hasSecurityNotion
Indicates that one entity possesses, defines, or is associated with a particular concept or notion of security in relation to another entity or context.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
| PDg | Predicate description generation | batch_69fd6dbc3ac0819093fbcfe95f12b93d |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 27, 2026, 10:03 p.m.