Triple
T17171197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Price |
E416736
|
entity |
| Predicate | initialSituation |
P31333
|
FINISHED |
| Object | struggling to keep the family shoe factory open |
—
|
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: struggling to keep the family shoe factory open | Statement: [Charlie Price, initialSituation, struggling to keep the family shoe factory open]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialSituation Context triple: [Charlie Price, initialSituation, struggling to keep the family shoe factory open]
-
A.
openingSituation
chosen
Indicates the initial state, context, or set of conditions that exist at the beginning of an event, interaction, or narrative.
-
B.
initialStatus
Indicates the original or starting state assigned to an entity before any changes or updates occur.
-
C.
initialOpening
Indicates the first or earliest instance in which something is opened, begun, or made accessible.
-
D.
initialGoal
Indicates that something represents the first or starting objective or target in a sequence of goals.
-
E.
initialAttitude
Indicates the starting stance, feeling, or disposition one entity holds toward another or toward a situation before any interaction or change occurs.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc097950819095631ee5679e03af |
completed | April 18, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.