Triple
T30579959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ground Zero |
E778355
|
entity |
| Predicate | notableStructureOnSite |
P57645
|
FINISHED |
| Object | One World Trade Center |
E745
|
NE 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: One World Trade Center | Statement: [Ground Zero, notableStructureOnSite, One World Trade Center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableStructureOnSite Context triple: [Ground Zero, notableStructureOnSite, One World Trade Center]
-
A.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
B.
notableBuildingAssociated
chosen
Indicates a relationship where a notable or significant building is associated with, connected to, or relevant to a given entity.
-
C.
notableSiteAssociatedWith
Indicates that there is a significant or noteworthy site or location that is associated with, related to, or prominently linked to the given entity.
-
D.
notableLocationOn
Indicates that a particular location is especially significant or noteworthy in relation to a specified entity or context.
-
E.
notableLocationFeature
Indicates that a location is characterized or distinguished by a particular notable physical or contextual feature.
- F. None of above.
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_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2870dc8e708190b95fc77f00591801 |
completed | June 9, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:23 p.m.