Triple
T15069894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sofía Henríquez Bachelet |
E379846
|
entity |
| Predicate | hasLowProfile |
P42756
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sofía Henríquez Bachelet, hasLowProfile, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowProfile Context triple: [Sofía Henríquez Bachelet, hasLowProfile, true]
-
A.
hasLow
Indicates that an entity possesses a value, level, or amount of something that is below a defined or expected threshold.
-
B.
hasLowForm
Indicates that an entity possesses a lower or less developed form, version, or level of something relative to a standard or comparison.
-
C.
hasLowerBarLength
Indicates that one entity’s bar length is shorter than the bar length of another entity.
-
D.
keptLowPublicProfile
chosen
Indicates that an entity deliberately maintained minimal visibility or attention in public or media contexts.
-
E.
hasLowLuminosity
Indicates that an entity emits relatively little light or energy compared to a typical or reference level.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7f86df48190b3a2cf441fefb477 |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.