Triple
T32125013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Martin Castillo |
E820474
|
entity |
| Predicate | screenPersonality |
P23367
|
FINISHED |
| Object | laconic |
—
|
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: laconic | Statement: [Lieutenant Martin Castillo, screenPersonality, laconic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenPersonality Context triple: [Lieutenant Martin Castillo, screenPersonality, laconic]
-
A.
personalityType
chosen
Indicates the specific psychological or behavioral profile that characterizes an entity’s typical patterns of thinking, feeling, and acting.
-
B.
featuresPsychicCharacter
Indicates that the subject includes or involves a character who possesses psychic or telepathic abilities.
-
C.
featuresNumberOfPersonalities
Indicates that an entity is characterized by or contains a specified number of distinct personalities.
-
D.
hasDifferentPersonalityIn
Indicates that an entity exhibits a different personality or character traits within a specified context, setting, or situation.
-
E.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another 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_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 12:29 a.m.