Triple
T12671357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arconia apartment building |
E302688
|
entity |
| Predicate | hasFeatureInFiction |
P106216
|
FINISHED |
| Object | courtyard |
—
|
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: courtyard | Statement: [Arconia apartment building, hasFeatureInFiction, courtyard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeatureInFiction Context triple: [Arconia apartment building, hasFeatureInFiction, courtyard]
-
A.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
-
B.
hasRelativeInFiction
Indicates that one entity has a relative or family member who appears as a character within a fictional work associated with the other entity.
-
C.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
D.
hasGroundsInFiction
Indicates that something is based on, justified by, or finds its origin within fictional works or narratives.
-
E.
hasChildInFiction
Indicates that a fictional work or character includes another character as their child within the fictional narrative.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:20 p.m.