Triple
T14574433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megan Walsh |
E342002
|
entity |
| Predicate | undercoverAs |
P20150
|
FINISHED |
| Object | high school student |
—
|
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: high school student | Statement: [Megan Walsh, undercoverAs, high school student]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undercoverAs Context triple: [Megan Walsh, undercoverAs, high school student]
-
A.
undercoverAgainst
Indicates that one entity is secretly acting in a covert or deceptive capacity directed against another entity.
-
B.
disguisedAs
chosen
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
C.
unawareOfTrueIdentityOf
Indicates that one entity does not know or recognize the real or actual identity of another entity.
-
D.
secretlyAssists
Indicates that one entity provides help or support to another without the knowledge of the recipient or relevant third parties.
-
E.
usesMasksOrDisguises
Indicates that an entity employs masks, costumes, or other forms of disguise to conceal or alter its identity in the context of an action or interaction.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f49d58819094fcd2a702e146cb |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.