Triple
T9299241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Macon (ZRS-5) |
E223717
|
entity |
| Predicate | wreckLocationStatus |
P87920
|
FINISHED |
| Object | protected archaeological site |
—
|
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: protected archaeological site | Statement: [USS Macon (ZRS-5), wreckLocationStatus, protected archaeological site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wreckLocationStatus Context triple: [USS Macon (ZRS-5), wreckLocationStatus, protected archaeological site]
-
A.
wreckStatus
Indicates the condition or state of damage of an object, typically describing whether and how badly it has been wrecked.
-
B.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
C.
containsWreck
Indicates that one entity includes or holds within it the remains or wreckage of another entity.
-
D.
wreckDiscovery
Indicates that an entity discovers, finds, or identifies a wreck (such as a ruined or destroyed object, vehicle, or structure).
-
E.
wreckSalvaged
Indicates that a previously wrecked object or structure has been recovered or salvaged from its damaged or sunken state.
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08cf50cc8190a025f478dff4f9fd |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:36 p.m.