Triple
T24054797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ishinomaki City |
E595766
|
entity |
| Predicate | hasRecoveryFocus |
P154688
|
FINISHED |
| Object | coastal protection |
—
|
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: coastal protection | Statement: [Ishinomaki City, hasRecoveryFocus, coastal protection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecoveryFocus Context triple: [Ishinomaki City, hasRecoveryFocus, coastal protection]
-
A.
hasReconstructionFocus
Indicates that something is primarily concerned with or directed toward the process or goal of reconstruction.
-
B.
hasRestorationFocus
Indicates that something is primarily concerned with or directed toward restoration or repair.
-
C.
hasReplayabilityFocus
Indicates that something is designed or evaluated with an emphasis on being enjoyable or worthwhile to experience multiple times.
-
D.
hasLocationFocus
Indicates that the primary emphasis or relevance of something is centered on a specific location or place.
-
E.
hasCharacterFocus
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9d551288190a2b3b6c8c4f3c1b5 |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:22 p.m.