Triple
T15010591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrietta Lacks |
E377824
|
entity |
| Predicate | yearCellsCollected |
P116342
|
FINISHED |
| Object | 1951 |
—
|
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: 1951 | Statement: [Henrietta Lacks, yearCellsCollected, 1951]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearCellsCollected Context triple: [Henrietta Lacks, yearCellsCollected, 1951]
-
A.
collectedSpecimensIn
Indicates that an entity gathered or obtained specimens within a specified location or context.
-
B.
numberOfCells
Indicates the total count of individual cells associated with or contained in a given entity.
-
C.
coinsCollectedFor
Indicates that a certain number of coins has been gathered or accumulated in order to benefit or be used for a particular entity or purpose.
-
D.
collectionSize
Indicates the total number of items contained within a specified collection.
-
E.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded734943481908dad4ceed4fe850c |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:55 a.m.