Triple
T30579900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9/11 Memorial pools |
E778354
|
entity |
| Predicate | victimNamesArrangement |
P170467
|
FINISHED |
| Object | meaningful adjacencies |
—
|
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: meaningful adjacencies | Statement: [9/11 Memorial pools, victimNamesArrangement, meaningful adjacencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimNamesArrangement Context triple: [9/11 Memorial pools, victimNamesArrangement, meaningful adjacencies]
-
A.
victimOrder
Indicates the sequence or ranking of victims involved in an event or incident.
-
B.
victimFullName
Indicates the complete personal name of the individual who is the victim in the described event or relationship.
-
C.
victimTitle
Indicates that one entity holds a title, role, or designation specifically in the capacity of being a victim in relation to another entity or event.
-
D.
victimAlias
Indicates that an entity is known or referred to by an alternative name specifically in the role of a victim.
-
E.
victimTitleAtDeath
Indicates the formal title or position held by the victim at the time of their death.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f69063edbc81909e7735954aabee0b |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68f6584a88190a8c4d95c0c84bee9 |
completed | May 2, 2026, 11:57 p.m. |
Created at: April 29, 2026, 8:23 p.m.