Triple
T21083900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Embassy in Tehran |
E519438
|
entity |
| Predicate | reasonForSeizure |
P694
|
FINISHED |
| Object | protest against U.S. support for Mohammad Reza Pahlavi |
—
|
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: protest against U.S. support for Mohammad Reza Pahlavi | Statement: [U.S. Embassy in Tehran, reasonForSeizure, protest against U.S. support for Mohammad Reza Pahlavi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForSeizure Context triple: [U.S. Embassy in Tehran, reasonForSeizure, protest against U.S. support for Mohammad Reza Pahlavi]
-
A.
locationOfSeizure
Indicates the place or setting where a seizure event occurs.
-
B.
methodOfSeizure
Indicates the manner or technique by which something is taken, captured, or seized.
-
C.
hasTypicalSeizureType
Indicates that an entity is associated with or characterized by a particular usual or predominant type of seizure.
-
D.
dateOfSeizure
Indicates the specific date on which a seizure (such as confiscation or legal taking of property) occurred.
-
E.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e70948704481908b8b75a2ecc42bb6 |
completed | April 21, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69e5dbfcd5e881908f1e4e0d2d237856 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:49 p.m.