Triple
T28544071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Hennessy |
E722379
|
entity |
| Predicate | artCharacteristics |
P164622
|
FINISHED |
| Object | introspective mood |
—
|
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: introspective mood | Statement: [Patrick Hennessy, artCharacteristics, introspective mood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artCharacteristics Context triple: [Patrick Hennessy, artCharacteristics, introspective mood]
-
A.
formatCharacteristics
Indicates how something is structured, arranged, or presented in terms of its format or layout.
-
B.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
-
C.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
-
D.
eraCharacteristic
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given historical or temporal era.
-
E.
castCharacteristic
Indicates that a particular characteristic or attribute is associated with, or defines, a cast or group of performers.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6500c24688190af625c85310438c8 |
completed | May 2, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64db8ee1881909362701d72ffe282 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 28, 2026, 3:37 a.m.