Triple
T11601843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eames House |
E275148
|
entity |
| Predicate | caseStudyNumber |
P100547
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Eames House, caseStudyNumber, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseStudyNumber Context triple: [Eames House, caseStudyNumber, 8]
-
A.
caseNumber
Indicates the unique identifying number assigned to a particular legal or administrative case.
-
B.
hasCaseStudy
Indicates that one entity is documented, illustrated, or analyzed by a specific case study associated with it.
-
C.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
D.
opusNumber
Indicates that a creative work is assigned a specific opus number identifying its place within a creator’s catalog or chronological sequence of works.
-
E.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8954daa908190a8d532e43aa4a881 |
completed | April 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69d87f2e67108190ac36bf47aac12fa8 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:38 p.m.