Triple
T15977551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Munroe |
E387485
|
entity |
| Predicate | notableLocationAssociated |
P78460
|
FINISHED |
| Object | abandoned sanatorium |
—
|
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: abandoned sanatorium | Statement: [Mike Munroe, notableLocationAssociated, abandoned sanatorium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLocationAssociated Context triple: [Mike Munroe, notableLocationAssociated, abandoned sanatorium]
-
A.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
B.
notableLocationDocumented
Indicates that a specific location associated with an entity is recorded or documented as notable in some source or reference.
-
C.
notableSiteAssociatedWith
chosen
Indicates that there is a significant or noteworthy site or location that is associated with, related to, or prominently linked to the given entity.
-
D.
notableLocationFeatured
Indicates that a particular location is prominently highlighted or showcased in relation to the subject.
-
E.
notableLocationFeature
Indicates that a location is characterized or distinguished by a particular notable physical or contextual feature.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.