Triple
T36781976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamie Graham |
E908795
|
entity |
| Predicate | internedIn |
P127153
|
FINISHED |
| Object | Lunghua Civilian Assembly Center |
—
|
NE NERFINISHED |
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: Lunghua Civilian Assembly Center | Statement: [Jamie Graham, internedIn, Lunghua Civilian Assembly Center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: internedIn Context triple: [Jamie Graham, internedIn, Lunghua Civilian Assembly Center]
-
A.
wasInternedAt
chosen
Indicates that a person was forcibly confined or detained at a particular place or facility, typically during a specific period.
-
B.
internedGroups
Indicates that certain groups of entities were confined or detained together, typically under restrictive or custodial conditions.
-
C.
usedToIntern
Indicates that one entity previously held an internship position with another entity.
-
D.
isInternal
Indicates that something exists or occurs within the boundaries, structure, or inner context of a specified entity or system, rather than being external to it.
-
E.
integratedIn
Indicates that one entity is incorporated as a component or part within a larger system, structure, or context represented by another entity.
- 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_69f76e798aa08190ace31098d1b13e9f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69feabcda59481908f2bc13b46fcced1 |
completed | May 9, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69feaabd63f88190b30dcf6dd2ea39d1 |
completed | May 9, 2026, 3:32 a.m. |
Created at: May 3, 2026, 4:12 p.m.